With the public availability of biochemical assays and screening data constantly increasing, new applications for data mining and method analysis are evolving in parallel. One example is BioAssay Ontology (BAO) for systematic classification of assays based on screening setup and metadata annotations. In this article we report a high-throughput screening (HTS) against phospho-N-acetylmuramoyl-pentapeptide translocase (MraY), an attractive antibacterial drug target involved in peptidoglycan synthesis. The screen resulted in novel chemistry identification using a fluorescence resonance energy transfer assay. To address a subset of the false positive hits, a frequent hitter analysis was performed using an approach in which MraY hits were compared with hits from similar assays, previously used for HTS. The MraY assay was annotated according to BAO and three internal reference assays, using a similar assay design and detection technology, were identified. Analyzing the assays retrospectively, it was clear that both MraY and the three reference assays all showed a high false positive rate in the primary HTS assays. In the case of MraY, false positives were efficiently identified by applying a method to correct for compound interference at the hit-confirmation stage. Frequent hitter analysis based on the three reference assays with similar assay method identified additional false actives in the primary MraY assay as frequent hitters. This article demonstrates how assays annotated using BAO terms can be used to identify closely related reference assays, and that analysis based on these assays clearly can provide useful data to influence assay design, technology, and screening strategy.